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Formulation of A Sale Price Prediction Model Based on Fuzzy Regression Analysis

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Operations Research Proceedings 2011

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

It is indispensable for companies to take some marketing strategy to predict and analyze the sale price met to customer satisfaction. In sale price prediction model, human factors are included in the elements composing the model, and it is getting more difficult to define and describe entire systems precisely. Therefore in case we obtain data from such a model, the data are accompanied by human subjective and experiential uncertainty. In this paper, we develop a theoretical formulation of sale price prediction model based on fuzzy regression with fuzzy input-output data (SPP-model). The solutions of SPP-model is found by solving two LP problems, both Min- and Max-problems, and each of them indicates upper and lower bounds of possibility for solutions (prices).

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References

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Author information

Authors and Affiliations

  1. Hokkai-Gakuen University, 1-40 Asahimachi, Toyohira-ku, Sapporo, 062-8605, Japan

    Michihiro Amagasa

Authors
  1. Michihiro Amagasa
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Correspondence to Michihiro Amagasa .

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Editors and Affiliations

  1. Institut für, Betriebswirtschaftslehre, Universität Zürich, Moussonstrasse, Zurich, 8044, Switzerland

    Diethard Klatte

  2. Inst. Operations Research, ETH Zürich, Rämistr. 101, Zürich, 8092, Switzerland

    Hans-Jakob Lüthi

  3. Institut für, Betriebswirtschaftslehre, Universität Zürich, Moussonstrasse 15, Zurich, 8044, Switzerland

    Karl Schmedders

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Amagasa, M. (2012). Formulation of A Sale Price Prediction Model Based on Fuzzy Regression Analysis. In: Klatte, D., Lüthi, HJ., Schmedders, K. (eds) Operations Research Proceedings 2011. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29210-1_90

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